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1,868 results for “Spatial Data”
Data from: Fine scale spatial variability in the influence of environmental cycles on the occurrence of dolphins at coastal sites
Environmental cycles often influence the presence of animals, creating patterns at different temporal scales, which may mean that their effects overlap and/or interact. Interactions between diel and seasonal cycles have been reported to influence fish behaviour but little is known about such interactions in marine top predators. Here, we studied the combined effect of seasonal, tidal and diel cycles on the occurrence of bottlenose dolphins (Tursiops truncatus) within a Marine Protected Area in Scotland. Our analyses were based on echolocation detections from passive acoustic devices (CPODs) deployed at three coastal sites between 2010 and 2016. We described patterns of dolphins' occurrence using circular statistics and then used generalised additive mixed models to explore the relative importance of each cycle and any interactions between them. We found site-specific cyclical patterns of presence that remained constant across years. There was a highly significant interaction between seasonal and diel cycles at two sites around deep channels, where occurrence was diurnal in summer but became nocturnal in autumn. The study demonstrates the highly plastic behaviour of bottlenose dolphins and shows a previously unreported behaviour that has management implications for this and other marine protected areas.
Data from: Linking habitat composition, local population densities and traffic characteristics to spatial patterns of ungulate-train collisions
1. Total length of railways worldwide exceeds 1 million kilometres and recent railway development directly impacts wildlife because of animal-train collisions. Few studies, however, have analysed factors driving ungulate-train collisions. 2. We analysed over 3500 ungulate-train collisions including roe deer, red deer, wild boar, and moose collected in 2012-2015 in Poland. We compared train traffic characteristics (e.g. traffic intensity, speed, rail curvature), land-use and habitat characteristics (e.g. share of forests and build-up areas) and local ungulate population densities at collision sites and random sites distributed along the rail network. 3. Forest coverage generally increased, while urban areas decreased ungulate collision risk. Local density of ungulate species was strongly positively related to the relative collision risk in all four ungulate species, but above certain densities, the risk levelled off for all four species. 4. Train speed and train traffic intensity were positively associated with elevated collision risk in all four species, but the latter in a non-linear manner reached an asymptote at the level of ca. 10 trains per day. Rail curvature also increased probability of collisions with roe deer and red deer and possibly also wild boar. 5. Mortality rate of ungulates on railways in Poland is estimated to be 0.13-0.42% of annual hunting bags of studied species assuming that only one individual is killed at each occasion and ignoring undetected collisions. These values are expected to increase in near future due to increasing train speed in Central European countries. 6. Synthesis and applications. Ungulate-train collisions spots are characterised by surrounding forest, rail curvature, high train speed, and a moderate to high train traffic intensity. To reduce collision risk in a cost-effective way, we suggest to prioritise mitigation actions at sections of the railway characterized by those factors, e.g. by fencing and various warning devices. Due to nonlinear correlation between collision risk and population density, reducing density of ungulates will most likely reduce collision risk only marginally, and only in regions of low population densities where collision risk is relatively low anyway.
Data from: Evaluating tools for the spatial management of fisheries
1. The ability to define the spatial dynamics of fish stocks is critical to fisheries management. Combating illegal, unreported and unregulated (IUU) fishing and the implementation of area based management through physical patrols and port side controls are growing areas of management attention. Augmenting the existing approaches to fisheries management with forensic techniques has the potential to increase compliance and enforcement success rates. 2. We tested the accuracy of three techniques that can be used to identify geographic origin (genotyping, otolith microchemistry and morphometrics). We used fish caught from three fishing grounds separated by a minimum of 5km and a maximum of 60km to list the accuracy of these approaches at relatively small spatial scales. 3. Using nearest-neighbor analyses, morphometric analysis was the most accurate (79.5%) in assigning individual fish to their fishing ground of origin. Neither otolith microchemistry (54.0%) or genetic analyses (52.4%) had sufficient assignment accuracy at the spatial scales we examined. 4. The combination of accuracy and minimal resource requirements make morphometric analyses a promising tool for assessing compliance with area based fishing restrictions at the scale of kilometers and have promising application especially in small scale fisheries through to community-based management approaches where technical and financial resources are limited.22-Jun-2018
Data from: Phylogenetically informed spatial planning is required to conserve the mammalian tree of life
In the face of the current extinction crisis and severely limited conservation resources, safeguarding the tree of life is increasingly recognized as a high priority. We conducted a first systematic global assessment of the conservation of phylogenetic diversity (PD) that uses realistic area targets and highlights the key areas for conservation of the mammalian tree of life. Our approach offers a substantially more effective conservation solution than one focused on species. In many locations, priorities for PD differ substantially from those of a species-based approach that ignores evolutionary relationships. This discrepancy increases rapidly as the amount of land available for conservation declines, as does the relative benefit for mammal conservation (for the same area protected). This benefit is equivalent to an additional 5900 Myr of distinct mammalian evolution captured simply through a better informed choice of priority areas. Our study uses area targets for PD to generate more realistic conservation scenarios, and tests the impact of phylogenetic uncertainty when selecting areas to represent diversity across a phylogeny. It demonstrates the opportunity of using rapidly growing phylogenetic information in conservation planning and the readiness for a new generation of conservation planning applications that explicitly consider the heritage of the tree of life's biodiversity.
Data from: Spatial memory shapes migration and its benefits: evidence from a large herbivore
From fine-scale foraging to broad-scale migration, animal movement is shaped by the distribution of resources. There is mounting evidence, however, that learning and memory also guide movement. Although migratory mammals commonly track resource waves, how resource tracking and memory guide long-distance migration has not been reconciled. We examined these hypotheses using movement data from four populations of migratory mule deer (n=91). Spatial memory had an extraordinary influence on migration, affecting movement 2–28 times more strongly than tracking spring green-up or autumn snow depth. Importantly, with only an ability to track resources, simulated deer were unable to recreate empirical migratory routes. In contrast, simulated deer with memory of empirical routes, used those routes and obtained higher foraging benefits. For migratory terrestrial mammals, spatial memory provides knowledge of where seasonal ranges and migratory routes exist, while resource tracking determines when to beneficially move within those areas.
Data from: Predicted effects of climate factors on mountain species are not uniform over different spatial scales
The selection of relevant factors and appropriate spatial scale(s) is fundamental when modelling species response to climate change. We evaluated whether the effects of climate factors on species distribution/occurrence are consistently modelled over different spatial scales in birds, and used a two-scale approach to identify species-climate correlations unlikely to represent causal effects. We used passerine birds inhabiting mountain grassland in the Apennines (Italy) as a model. We surveyed four grassland species at 400 sampling points, and built habitat selection models (territory scale) and distribution models (7 algorithms, landscape scale). We compared the effect of climatic predictors on occurrence/distribution highlighted by models over to the two spatial scales, and with the effects supposed a priori based on the climatic niche of each species. Models at the territory level included at least one climatic predictor for three species; the observed effect of climatic predictors was seldom consistent with supposed effects. At the broadest scale, distribution models for all species included climatic predictors, with varying consistence with supposed effects and findings at the finer scale. Despite the importance of climate for species distribution, occurrence could be more directly related to other factors, with important implications for understanding/predicting the impacts of climate/environmental changes. Our approach revealed key variables for grassland birds, and highlighted the scale-dependent perceived importance of climate. At the local scale, climate effects were weak or hard to interpret. We found a general lack of consistence between supposed and observed effects at the territory level, and between landscape and territory models. Our results show the importance of predicting the potential effect of climatic factors prior to the analyses, carefully selecting ecologically meaningful variables and scales, and evaluating the nature and scale of climate-species links. We call for caution when predicting under future climates, especially when mechanistic effects and consistency across scales lack.
Data from: Spatial variation in anuran richness, diversity, and abundance across montane wetland habitat in Volcanoes National Park, Rwanda
The spatial distribution of species has long sparked interest among ecologists and biogeographers, increasingly so in studies of species responses to climate change. However, field studies on spatial patterns of distribution, useful to inform conservation actions at local scales, are still lacking for many regions, especially the tropics. We studied elevational trends and species‐area relationships among anurans in wetland habitats within Volcanoes National Park (VNP) in Rwanda, part of the biodiverse Albertine Rift region. In VNP, wetlands are key sites for anuran reproduction, and anurans are likely threatened by wetland desiccation which has occurred for the last few decades. Between 2012 and 2017, we sampled anuran communities in ten VNP wetlands located along an elevational gradient of c. 600 m (from 2,546 to 3,188 m a.s.l.) and found at least eight species, including at least two Albertine Rift Endemics. We show that species richness, diversity, and abundance likely decline with a decrease in wetland size and with an increase in elevation, though additional sampling (e.g., at night) might be needed to derive definite conclusions. Larger wetlands at lower elevations contained most species and individuals, which indicates the potential threat of wetland size reduction (through desiccation) for anuran conservation. However, we also found that wetlands differed in species composition and that some species (e.g., Sclerophrys kisoloensis) were likely restricted in distribution to only a few of the smaller wetlands—suggesting that the conservation of each individual wetland should be prioritized, regardless of size. We propose that all wetlands in VNP require additional conservation measures, which should be based on knowledge gathered through long‐term monitoring of anuran communities and research on drivers of wetland decline. Only such extended research will allow us to understand the response of anurans in VNP to threats such as climate change and wetland desiccation.
Data from: Comparison of spatial and temporal genetic differentiation in a harmful dinoflagellate species emphasises impact of local processes
Population genetic studies provide insights into intraspecific diversity and dispersal patterns of microorganisms such as protists, which help understanding invasions, harmful algal bloom development and occurrence of seafood poisoning. Genetic differentiation across geography has been reported in many microbial species indicating significant dispersal barriers among different habitats. Temporal differentiation has been less studied and its frequency, drivers and magnitude are poorly understood due to a lack of integral studies. The toxic dinoflagellate species /Gambierdiscus caribaeus/ was sampled during two years in the Florida Keys, and repeatedly from 2006 to 2016 at St. Thomas, US Virgin Islands (USVI), including a three-year period with monthly sampling, to compare spatial and temporal genetic differentiation. Samples from the USVI site showed high temporal variability in local population structure, which correlated with changes in salinity and benthic habitat cover. In some cases, temporal variability exceeded spatial differentiation, despite apparent lack of connectivity and dispersal across the Greater Caribbean Region based on the spatial genetic data. Thus, local processes such as selection might have a stronger influence on population structure in microorganisms than geographic distance. The observed high temporal genetic diversity challenges the prediction of harmful algal blooms and toxin concentrations, but illustrates also the evolutionary potential of microalgae to respond to environmental change.
Data from: Do spatial scale and life history affect fish-habitat relationships?
1. Understanding how animals interact with their environment is a fundamental ecological question with important implications for conservation and management. The relationships between animals and their habitat, however, can be scale dependent. If ecologists work at suboptimal spatial scales, they will gain an incomplete picture of how animals respond to the landscape. Identifying the scale at which animal-landscape relationships are strongest (the 'scale of effect') will improve our ability to better plan management and conservation activities. 2. Several recent studies have greatly enhanced our knowledge about the scale of effect, and the potential drivers of inter-specific variability, in particular life-history traits. However, while many marine systems are inherently multi-scalar, research into the scale of effect has been mainly focussed on terrestrial taxa. As the scales of observation in fish-habitat association studies are often selected based on convention rather than biological reasoning, they may provide an incomplete picture of the scales where these associations are strongest. 3. We examined fish-habitat associations across four nested spatial scales in a temperate reef system to ask: (1.) at what scale are fish-habitat associations the strongest, (2.) are habitat elements consistently important across scales, and (3.) do scale-dependent fish-habitat associations vary in relation to either body size, geographic range size or trophic level? 4. We found that: (1.) the strongest fish-habitat associations were observed when these relationships were examined at considerably larger spatial scales than usually investigated; (2.) the importance of environmental predictors varied across spatial scales, indicating that conclusions about the importance of habitat elements will depend on the scales at which studies are undertaken; and (3.) scale-dependent fish-habitat associations were consistent across all life-history traits. 5. Our results highlight the importance of considering how animals relate to their environment and suggest the small scales often chosen to examine fish-habitat associations are likely to be suboptimal. Developing a more mechanistic understanding of animal-habitat associations will greatly aid in predicting and managing responses to future anthropogenic disturbances.
Data from: Genetic relatedness does not retain spatial pattern across multiple spatial scales: dispersal and colonization in the coral, Pocillopora damicornis
Patterns of isolation-by-distance are uncommon in coral populations. Here, we depart from historical trends of large-scale, geographic genetic analyses by scaling down to a single patch reef in Kāne'ohe Bay, Hawai'i, and map and genotype all colonies of the coral, Pocillopora damicornis. Six polymorphic microsatellite loci were used to assess population genetic and clonal structure and to calculate individual colony pairwise relatedness values. Our results point to an inbred, highly clonal reef (between 53 and 116 clonal lineages out of 2352 genotyped colonies) with a very skewed genet frequency distribution (over 70% of the reef was composed of just seven genotypes). Spatial autocorrelation analyses revealed that corals found close together on the reef were more genetically related than corals further apart. Spatial genetic structure disappears, however, as spatial scale increases and then becomes negative at the largest distances. Stratified, random sampling of three neighbouring reefs confirms that reefs are demographically open and inter-reef genetic structuring was not detected. Attributing process to pattern in corals is complicated by their mixed reproductive strategies. Separate autocorrelation analyses, however, show that the spatial distribution of both clones and non-clones contribute to spatial genetic structure. Overall, we demonstrate genetic structure on an intra-reef scale and genetic panmixia on an inter-reef scale indicating that, for P. damicornis, small- and large-scale dispersal processes are likely not the same. By starting from an inter-individual, intra-reef level before scaling up to an inter-reef level, this study demonstrates that isolation-by-distance patterns for the coral P. damicornis are limited to small scales and highlights the importance of investigating genetic patterns and ecological processes at multiple scales.
Data from: Using camera trapping and hierarchical occupancy modelling to evaluate the spatial ecology of an African mammal community
Emerging conservation paradigms have shifted from single to multi-species approaches focused on sustaining biodiversity. Multi-species hierarchical occupancy modelling provides a method for assessing biodiversity while accounting for multiple sources of uncertainty. We analysed camera trapping data with multi-species models using a Bayesian approach to estimate the distributions of a terrestrial mammal community in northern Botswana and evaluate community, group, and species-specific responses to human disturbance and environmental variables. Groupings were based on two life-history traits: body size (small, medium, large and extra-large) and diet (carnivore, omnivore and herbivore). We photographed 44 species of mammals over 6607 trap nights. Camera station-specific estimates of species richness ranged from 8 to 27 unique species, and species had a mean occurrence probability of 0·32 (95% credible interval = 0·21–0·45). At the community level, our model revealed species richness was generally greatest in floodplains and grasslands and with increasing distances into protected wildlife areas. Variation among species' responses was explained in part by our species groupings. The positive influence of protected areas was strongest for extra-large species and herbivores, while medium-sized species actually increased in the non-protected areas. The positive effect of grassland/floodplain cover, alternatively, was strongest for large species and carnivores and weakest for small species and herbivores, suggesting herbivore diversity is promoted by habitat heterogeneity. Synthesis and applications. Our results highlight the importance of protected areas and grasslands in maintaining biodiversity in southern Africa. We demonstrate the utility of hierarchical Bayesian models for assessing community, group and individual species' responses to anthropogenic and environmental variables. This framework can be used to map areas of high conservation value and predict impacts of land-use change. Our approach is particularly applicable to the growing number of camera trap studies world-wide, and we suggest broader application globally will likely result in reduced costs, improved efficiency and increased knowledge of wildlife communities.
Data from: The landscape of anthropogenic mortality: how African lions respond to spatial variation in risk
1. Demography and conservation status of many wild organisms are increasingly shaped by interactions with humans. This is particularly the case for large, wide ranging carnivores. 2. Using 206 mortality records (1999-2012) of lions in Hwange National Park, Zimbabwe, we calculated mortality rates for each source of anthropogenic mortality, modelled risk of anthropogenic mortality across the landscape accounting for time lions spent in different parts of the landscape, and assessed whether subsets of the population were more at risk. 3. Anthropogenic activities caused 88% of male and 67% of female mortalities; male mortality being dominated by trophy hunting while the sources for female mortality were more varied (snaring, retaliatory killing, hunting). 4. Landscapes of anthropogenic mortality risk revealed that communal subsistence farming areas, characterized by high risk (due to retaliatory killing) but avoided by lions, are population sinks. Trophy hunting areas and areas within protected areas bordering communal farmland, where bush-meat snaring is prevalent, form 'ecological traps' (or 'attractive sinks'). 5. Lions avoided risky areas, suggesting they may make behavioural decisions based on perceptions of risk. Experienced adults used risky areas less and incorporated lower proportions of them in their home ranges than young individuals, suggesting that the latter may either be naïve or forced into peripheral habitats. Synthesis and applications: This paper contributes to an understanding of the way in which carnivore populations are affected by anthropogenic mortality across the conservation landscape. This is critical to designing focussed, appropriate and cost effective conservation management strategies. Agricultural areas are intuitively identified by conservationists as being risky for carnivores due to retaliatory or pre-emptive killing, with threats largely mitigated against by improving livestock protection. However, parts of protected areas may also form less easily identified 'attractive sinks' for carnivores. In particular, trophy hunting adjacent to national parks needs careful management to avoid damaging effects of overhunting. Law enforcement is needed to reduce the effects of bush-meat poaching on predators and other wildlife in protected areas. To be most effective, resource limited anti-poaching activities should prioritise wildlife rich areas close to human settlement as these tend to be hotspots for bush-meat poaching.
Data from: Fine-scale spatial genetic dynamics over the life-cycle of the tropical tree Prunus africana
Studying fine-scale spatial genetic patterns across life stages is a powerful approach to identify ecological processes acting within tree populations. We investigated spatial genetic dynamics across five life stages in the insect-pollinated and vertebrate-dispersed tropical tree Prunus africana in Kakamega Forest, Kenya. Using six highly polymorphic microsatellite loci, we assessed genetic diversity and spatial genetic structure (SGS) from seed rain and seedlings, and different sapling stages to adult trees. We found significant SGS in all stages, potentially caused by limited seed dispersal and high recruitment rates in areas with high light availability. SGS decreased from seed and early seedling stages to older juvenile stages. Interestingly, SGS was stronger in adults than in late juveniles. The initial decrease in SGS was probably driven by both random and non-random thinning of offspring clusters during recruitment. Intergenerational variation in SGS could have been driven by variation in gene flow processes, overlapping generations in the adult stage or local selection. Our study shows that complex sequential processes during recruitment contribute to SGS of tree populations.
Data from: Spatial and seasonal influences on culturable endophytic mycobiota associated with different tissues of Eugenia jambolana Lam. and their antibacterial activity against MDR strains
Background: Present study focuses on diversity and distribution analysis of endophytic fungi associated with different tissues of Eugenia jambolana. The influence of season and geographical location on diversity and distribution of endophytic fungi has been analyzed. Antibacterial activity of isolated fungal species has also been investigated against MDR bacterial strains. Result: A total of 1896 endophytic fungal isolates were obtained from healthy, surface sterilized tissues of leaf, stem and petiole tissues during summer, monsoon and winter season. Out of 24 fungal species isolated, 20 species belong to class Ascomycetes, 2 to Basidiomycetes and 2 to Zygomycetes. Maximum species diversity was in rainy season whereas colonization frequency was in winter. All the diversity indices showed maximum species diversity at site 5 (Yamunanager), rainy among the seasons and leaf among the tissues studied. Aspergillus genus was most frequently isolated. Aspergillus niger and Alternaria alternata were most dominant species. Three way ANOVA results showed that effect of season was highly significant on species diversity in relation to sites and tissues. 60% endophytic fungal extracts showed significant antibacterial activity against one or more than one MDR bacterial strain. Conclusion: Different fungal species were recovered from different sites but the inter-site comparisons were not significant according to Jaccard similarity coefficient. Diversity of such fungal endophytes indicates that Eugenia jambolana plant acts as an ecosystem facilitating survival of many microbes with impressive antibacterial potential.
Data from: High resolution spatial mapping of human footprint across Antarctica and its implications for the strategic conservation of avifauna
Human footprint models allow visualization of human spatial pressure across the globe. Up until now, Antarctica has been omitted from global footprint models, due possibly to the lack of a permanent human population and poor accessibility to necessary datasets. Yet Antarctic ecosystems face increasing cumulative impacts from the expanding tourism industry and national Antarctic operator activities, the management of which could be improved with footprint assessment tools. Moreover, Antarctic ecosystem dynamics could be modelled to incorporate human drivers. Here we present the first model of estimated human footprint across predominantly ice-free areas of Antarctica. To facilitate integration into global models, the Antarctic model was created using methodologies applied elsewhere with land use, density and accessibility features incorporated. Results showed that human pressure is clustered predominantly in the Antarctic Peninsula, southern Victoria Land and several areas of East Antarctica. To demonstrate the practical application of the footprint model, it was used to investigate the potential threat to Antarctica's avifauna by local human activities. Relative footprint values were recorded for all 204 of Antarctica's Important Bird Areas (IBAs) identified by BirdLife International and the Scientific Committee on Antarctic Research (SCAR). Results indicated that formal protection of avifauna under the Antarctic Treaty System has been unsystematic and is lacking for penguin and flying bird species in some of the IBAs most vulnerable to human activity and impact. More generally, it is hoped that use of this human footprint model may help Antarctic Treaty Consultative Meeting policy makers in their decision making concerning avifauna protection and other issues including cumulative impacts, environmental monitoring, non-native species and terrestrial area protection.
Data from: Spatially varying selection shapes life history clines among populations of Drosophila melanogaster from sub-Saharan Africa
Clines in life history traits, presumably driven by spatially varying selection, are widespread. Major latitudinal clines have been observed, for example, in Drosophila melanogaster, an ancestrally tropical insect from Africa that has colonized temperate habitats on multiple continents. Yet, how geographic factors other than latitude, such as altitude or longitude, affect life history in this species remains poorly understood. Moreover, most previous work has been performed on derived European, American and Australian populations, but whether life history also varies predictably with geography in the ancestral Afro-tropical range has not been investigated systematically. Here, we have examined life history variation among populations of D. melanogaster from sub-Saharan Africa. Viability and reproductive diapause did not vary with geography, but body size increased with altitude, latitude and longitude. Early fecundity covaried positively with altitude and latitude, whereas lifespan showed the opposite trend. Examination of genetic variance–covariance matrices revealed geographic differentiation also in trade-off structure, and QST-FST analysis showed that life history differentiation among populations is likely shaped by selection. Together, our results suggest that geographic and/or climatic factors drive adaptive phenotypic differentiation among ancestral African populations and confirm the widely held notion that latitude and altitude represent parallel gradients.
Data from: Optimizing the trade-off between spatial and genetic sampling efforts in patchy populations: towards a better assessment of functional connectivity using an individual-based sampling scheme
Genetic data are increasingly used in landscape ecology for the indirect assessment of functional connectivity, i.e. the permeability of landscape to movements of organisms. Among available tools, matrix correlation analyses (e.g. Mantel tests or mixed models) are commonly used to test for the relationship between pairwise genetic distances and movement costs incurred by dispersing individuals. When organisms are spatially clustered, a population-based sampling scheme (PSS) is usually performed, so that a large number of genotypes can be used to compute pairwise genetic distances on the basis of allelic frequencies. Because of financial constraints, this kind of sampling scheme implies a drastic reduction in the number of sampled aggregates, thereby reducing sampling coverage at the landscape level. We used matrix correlation analyses on simulated and empirical genetic datasets to investigate the efficiency of an individual-based sampling scheme (ISS) in detecting isolation-by-distance and isolation-by-barrier patterns. Provided that pseudo-replication issues are taken into account (e.g. through restricted permutations in Mantel tests), we showed that the use of inter-individual measures of genotypic dissimilarity may efficiently replace inter-population measures of genetic differentiation: the sampling of only three or four individuals per aggregate may be sufficient to efficiently detect specific genetic patterns in most situations. The ISS proved to be a promising methodological alternative to the more conventional PSS, offering much flexibility in the spatial design of sampling schemes and ensuring an optimal representativeness of landscape heterogeneity in data, with few aggregates left unsampled. Each strategy offering specific advantages, a combined use of both sampling schemes is discussed.
Data from: Spatial and ecological population genetic structures within two island-endemic Aeonium species of different niche width
The Crassulacean genus Aeonium is a well-known example for plant species radiation on oceanic archipelagos. However, while allopatric speciation among islands is documented for this genus, the role of intra-island speciation due to population divergence by topographical isolation or ecological heterogeneity has not yet been addressed. The aim of this study was to investigate intraspecific genetic structures and to identify spatial and ecological drivers of genetic population differentiation on the island scale. We analyzed inter simple sequence repeat variation within two island-endemic Aeonium species of La Palma: one widespread generalist that covers a large variety of different habitat types (Ae. davidbramwellii) and one narrow ecological specialist (Ae. nobile), in order to assess evolutionary potentials on this island. Gene pool differentiation and genetic diversity patterns were associated with major landscape structures in both species, with phylogeographic implications. However, overall levels of genetic differentiation were low. For the generalist species, outlier loci detection and loci–environment correlation approaches indicated moderate signatures of divergent selection pressures linked to temperature and precipitation variables, while the specialist species missed such patterns. Our data point to incipient differentiation among populations, emphasizing that ecological heterogeneity and topographical structuring within the small scales of an island can foster evolutionary processes. Very likely, such processes have contributed to the radiation of Aeonium on the Canary Islands. There is also support for different evolutionary mechanisms between generalist and specialist species.
Data from: Interaction networks of macrofungi and mycophagous beetles reflect diurnal variation and the size and spatial arrangement of resources
Ecological networks are useful for characterizing interspecific associations and predicting the resilience of ecological communities. We evaluated how such networks vary with the size, spatial distribution, and timing of availability of resources, with a focus on beetle-macrofungal associations. We used 2 y of field experiments to construct ecological networks based on manipulated sporocarp baits (resources; Pleurotus ostreatus) and natural communities of beetles (consumers) in a temperate forest. Centrality and interaction strength increased with resource size, but were associated weakly with resource density and isolation, and not at all with position within patches. Whole-network connectance was greater in mornings (when beetle richness and abundance were high) than evenings. Interannual differences in networks were consistent with differences in beetle communities between years. The capacity of networks to vary temporally, spatially, and as a function of resource traits is examined in light of understanding beetle-macrofungal associations, which are important components of fungal ecology.
Data from: Estimating density for species conservation: comparing camera trap spatial count models to genetic spatial capture-recapture models
Density estimation is integral to the effective conservation and management of wildlife. Camera traps in conjunction with spatial capture-recapture (SCR) models have been used to accurately and precisely estimate densities of "marked" wildlife populations comprising identifiable individuals. The emergence of spatial count (SC) models holds promise for cost-effective density estimation of "unmarked" wildlife populations when individuals are not identifiable. We evaluated model agreement, precision, and survey costs, between i) a fully marked approach using SCR models fit using non-invasive genetic data, and ii) an unmarked approach using SC models fit using camera trap data, for a recovering population of the mesocarnivore fisher (Pekania pennanti). The SCR density estimates ranged from 2.95 to 3.42 (2.18–5.19 95% BCI) fishers 100 km−2. The SC density estimates were influenced by their priors, ranging from 0.95 (0.65–2.95 95% BCI) fishers 100 km−2 for the uninformative model to 3.60 (2.01–7.55 95% BCI) fishers 100 km−2 for the model informed by prior knowledge of a 16 km2 fisher home range. We caution against using strongly informative priors but instead recommend using a range of unweighted prior knowledge. Thin detection data was problematic for both SCR and SC models, potentially producing biased low estimates. The total cost of the genetic survey ($47 610) was two-thirds of the camera trap survey ($77 080), or comparable ($75 746) if genetic sampling effort was increased to include sex and trap-behaviour covariates in SCR models. Density estimation of unmarked populations continues to be a series of trade-offs but as methods improve and integrate, so will our estimates.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.